On informational efficiency of the banking sector: a behavioral model of the credit boom

Purpose – This paper aims to examine the informational efficiency in retail credit markets to test whether behavioral biases (excessive optimism) by some participants in the banking industry might explain how credit booms are fueled by the banking sector. Design/methodology/approach – This paper analyzes the conditions for the efficient market hypothesis approach to be extended to bank-based systems. A simple model of herding and limits of arbitrage that follows a three-step behavioral approach is presented (Shleifer, 2000). The model is based on duopolistic Cournot competition, where one bank is unbiased and the other is boundedly rational in terms of excessive optimism. Findings – The paper shows why solely behavioral biases by participants in the banking industry explain how it feeds a credit bubble. According to the presented model, optimistic banks would lead the industry, while it would be rational for unbiased banks to herd under conditions that the authors derive. An important finding is the role of limits of arbitrage in the banking sector: there would be no incentives for rational banks to correct the misallocations of their biased competitors. Practical implications – It might be a valid contribution to the current debate on macroprudential regulation. Should tests of rationality and correlated behavior provide evidence on the pervasiveness of behavioral biases in the banking industry suggested by our model, then banking regulation should account for it. Originality/value – This paper introduces an alternative approach to analyze informational efficiency in the banking industry that, to the best of our knowledge, had not been raised so far. The model shows how behavioral biases might guide retail credit markets and why limits of arbitrage would be more pervasive in bank-based financial systems than in market-based ones.